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Erschienen in:
2018 | OriginalPaper | Buchkapitel
Identifying the Polypharmacy Side-Effects in Daily Life Activities of Elders with Dementia
verfasst von : Viorica Chifu, Cristina Pop, Tudor Cioara, Ionut Anghel, Dorin Moldovan, Ioan Salomie
Erschienen in: Intelligent Distributed Computing XII
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Abstract
This paper addresses the problem of polypharmacy management in older patients with dementia. We propose a technique that combines semantic technologies with big data machine learning techniques to detect deviations in daily activities which may signal the side effects of a drug-drug interaction. A polypharmacy management knowledge base was developed and used to semantically define drug-drug interactions and to annotate with the help of doctors significant registered deviations from the elders’ routines. The Random Forest Classifier is used to detect the days with significant deviations, while the k-means clustering algorithm is used to automate the deviations annotation process. The results are promising showing that such an approach can be successfully applied for assisting doctors in identifying the effects of polypharmacy in the case of patients with dementia.